{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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SNBKYBpwiadd8gFfKIOUA1Uc5SHwVOB/4R+C7wL8CH8iPN+QfLentwPeBj0XE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\ns1JygDIzs1JygDIzs1L6/yRIdrxMWns2AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10fbea160>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# %load Plot.py\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib \n",
    "%matplotlib inline\n",
    "\n",
    "f, (ax1, ax2) = plt.subplots(1, 2)\n",
    "#plt.suptitle('OPLS-AA/M in NAMD vs GMX')\n",
    "df = pd.read_csv('ANALYSIS_AXA.csv',delim_whitespace=True)\n",
    "df[['RES','BOND','ANGLE','DIHEDRAL','IMPROPER','VDWL']].plot(kind='box',ax=ax1,rot=45)\n",
    "ax1.set_ylabel('GMX - NAMD')\n",
    "df[['RES','ELEC','TOTAL']].plot(kind='box',ax=ax2,rot=41)\n",
    "ax2.set_ylabel('GMX - NAMD')\n",
    "#plt.show()\n",
    "plt.tight_layout()\n",
    "plt.savefig('RES.pdf')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "plt.tight_layout?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [default]",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
